{"id":"W2325435355","doi":"10.1190/1.3513119","title":"Neural network regression analysis and post‐stack inversion‐ A comparison","year":2010,"lang":"en","type":"article","venue":"","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"ARC Resources (Canada)","funders":"","keywords":"Reservoir modeling; Inversion (geology); Artificial neural network; Seismic inversion; Geology; Regression analysis; Regression; Seismology; Linear regression; Computer science; Artificial intelligence; Statistics; Mathematics; Machine learning; Geotechnical engineering; Geometry; Tectonics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009094756,0.00009138983,0.0001480136,0.00006346362,0.0002189627,0.0001543161,0.0003829728,0.00004854616,0.00004757875],"category_scores_gemma":[0.000005519863,0.00006419145,0.00006225939,0.000951072,0.00003999369,0.0002214343,0.000280102,0.000194799,0.00001558651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002864526,"about_ca_system_score_gemma":0.000007538675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006838999,"about_ca_topic_score_gemma":0.0002697654,"domain_scores_codex":[0.9992245,0.0000230781,0.0001448905,0.0002936486,0.0001227926,0.0001910327],"domain_scores_gemma":[0.9992351,0.00007633963,0.00006455731,0.0004468168,0.00004770618,0.0001294575],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002271282,0.0002164563,0.3666032,0.00001183949,0.0002150181,0.00001323482,0.0004748992,0.010196,0.01993483,0.1924773,0.1152438,0.2945908],"study_design_scores_gemma":[0.00009018827,0.0000242005,0.06614557,0.000002205948,0.0000352814,0.000003416959,0.000009575336,0.9270357,0.0002688742,0.000901752,0.005366512,0.0001167267],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8664058,0.00006049524,0.126221,0.005551427,0.0002359953,0.0001193824,8.707536e-7,0.000173458,0.001231517],"genre_scores_gemma":[0.9666144,0.000008062079,0.03202481,0.0009027594,0.00009653826,0.000004981741,0.00000520659,0.000003025744,0.0003402515],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9168397,"threshold_uncertainty_score":0.2617652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01310604111456134,"score_gpt":0.2668539388853214,"score_spread":0.2537478977707601,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}